scholarly journals An Intelligent Group Decision Evaluation Model with Interval-Valued Intuitionistic Fuzzy Entropy Technology for Microblog User Influence

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Lihua Zeng ◽  
Tonghua Yang ◽  
Haiping Ren ◽  
Neal Xiong
Keyword(s):  
Social Network ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Fuzzy Entropy ◽  
Evaluation Index System ◽  
Intuitionistic Fuzzy ◽  
User Influence ◽  
Intuitionistic Fuzzy Entropy ◽  
The Impact ◽  
Interval Valued

Aiming at the shortcomings of some existing interval-valued intuitionistic fuzzy entropy, this paper proposes an interval-valued intuitionistic fuzzy entropy, which contains not only the interval distance between membership and nonmembership but also the average hesitancy information. On this basis, the impact evaluation of microblog users is studied. Through the multilevel decomposition of user influence, the coverage of microblog, user interaction, and user activity are constructed as the first level indicators, and nine secondary indicators are selected as the comprehensive evaluation index system of microblog influence. Considering the highly dynamic and unstructured characteristics of social network data, the idea of interval-valued intuitionistic fuzzy is introduced to transform the evaluation of social network users’ influence into interval-valued intuitionistic fuzzy multiattribute group decision-making problem. Finally, the model is applied to dynamic evaluation of Sina Weibo users’ influence to verify the effectiveness of the model.

scholarly journals Intuitionistic Fuzzy Entropy for Group Decision Making of Water Engineering Project Delivery System Selection

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1101 ◽  
Author(s):  
Liu ◽  
Qian ◽  
Lin ◽  
Zhang ◽  
Zhu
Keyword(s):  
Delivery System ◽  
Group Decision ◽  
Weighted Average ◽  
Fuzzy Entropy ◽  
Project Delivery ◽  
Delivery Mode ◽  
Practical Case ◽  
Engineering Project ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy

The project delivery mode is an extremely important link in the life cycle of water engineering. Many cases show that increases in the costs, construction period, and claims in the course of the implementation of water engineering are related to the decision of the project delivery mode in the early stages. Therefore, it is particularly important to choose a delivery mode that matches the water engineering. On the basis of identifying the key factors that affect the decision on the project delivery system and establishing a set of index systems, a comprehensive decision of engineering transaction is essentially considered to be a fuzzy multi-attribute group decision. In this study, intuitionistic fuzzy entropy was used to determine the weight of the influencing factors on the engineering transaction mode; then, intuitionistic fuzzy entropy was used to determine the weight of decision experts. Thus, a comprehensive scheme-ranking model based on an intuitionistic fuzzy hybrid average (IFHA) operator and intuitionistic fuzzy weighted average (IFWA) operator was established. Finally, a practical case analysis of a hydropower station further demonstrated the feasibility, objectivity, and scientific nature of the decision model.

scholarly journals Humanitarian Rescue Scheme Selection under the Covid-19 Crisis in China: Based on Group Decision-Making Method

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 668
Author(s):  
Xiaotong Deng ◽  
Zhaojun Kong
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Scheme Selection ◽  
Interval Valued

Humanitarian rescue has become an important part of government emergency management in China. In order to select the optimal humanitarian rescue scheme accurately and in a timely manner in an emergency, reduce the harm of disasters to human life and health, and improve the government’s emergency management ability, a multi-attribute emergency group decision-making method is proposed. First, interval-valued intuitionistic fuzzy sets are used to express the preferences of decision-makers, and interval-valued intuitionistic fuzzy entropy is used to calculate attribute weights. Then, based on the technique for order preference by similarity to an ideal solution (TOPSIS) method, the weight of the decision-maker is calculated. Then, the relevant interval intuitionistic fuzzy operators are used to summarize the preferences of decision-makers in group decision-making. Finally, we will use the closeness ranking method to choose the optimal scheme, and the feasibility and practicability of the proposed method are demonstrated by an example. The example shows that the model is more scientific, objective, and comprehensive in solving the problem of multi-attribute group decision-making than the traditional scheme selection, which only depends on the subjective discussion of decision-makers.

scholarly journals Contingency Response Decision of Network Public Opinion Emergencies based on Intuitionistic Fuzzy Entropy and Preference Information of Decision Makers

2021 ◽  
Author(s):  
Sha Fu ◽  
Ye-zhi Xiao ◽  
Hang-jun Zhou
Keyword(s):  
Decision Making ◽  
Public Opinion ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Preference Information ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making ◽  
Network Public Opinion

Abstract A multi-attribute group decision-making (MAGDM) method based on intuitionistic fuzzy preference information is proposed for the multi-attribute intuitionistic fuzzy group decision-making problem where the decision-makers weight and attribute weight are completely unknown and the decision-maker has preference information for the scheme. Firstly, an intuitionistic fuzzy interval judgment matrix is established to describe the original data of the key decision indicators for multiple network public opinion emergencies that erupt simultaneously. Secondly, the attribute weights are determined based on the improved intuitionistic fuzzy entropy construction method, and the expert weights are determined by using objective decision information, taking into account the intuitionistic fuzzy entropy of decision matrix. Thirdly, a scheme preference model and an attribute weight optimization model are established to determine the ranking method of intuitionistic fuzzy interval values. Then, an improved intuitionistic fuzzy number distance measure is introduced to make the evaluation result more accurate and reasonable when it comes to solving the deviation between the evaluation value and ideal solution of each scheme. Finally, the effectiveness and practicability of the proposed decision-making method are verified by an example of emergency crisis severity, which improves the efficiency of emergency treatment, helps emergency departments to better deal with the network public opinion crisis, improves the ability of public opinion guidance and control, and provides a new method and idea for multi-attribute intuitionistic fuzzy group decision-making problem.

scholarly journals An Effective Interval-Valued Intuitionistic Fuzzy Entropy to Evaluate Entrepreneurship Orientation of Online P2P Lending Platforms

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaohong Chen ◽  
Li Yang ◽  
Pei Wang ◽  
Wei Yue
Keyword(s):  
Fuzzy Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Fuzzy Entropy ◽  
Evaluation Procedure ◽  
Entropy Measure ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Essential Properties ◽  
P2p Lending ◽  
Interval Valued

This paper describes an approach to measure the entrepreneurship orientation of online P2P lending platforms. The limitations of existing methods for calculating entropy of interval-valued intuitionistic fuzzy sets (IVIFSs) are significantly improved by a new entropy measure of IVIFS considered in this paper, and then the essential properties of the proposed entropy are introduced. Moreover, an evaluation procedure is proposed to measure entrepreneurship orientation of online P2P lending platforms. Finally, a case is used to demonstrate the effectiveness of this method.

scholarly journals A New Type of Compositive Information Entropy for IvIFS and Its Applications

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Junjun Mao ◽  
Yuan Zhao ◽  
Chuang Ma
Keyword(s):  
Intuitionistic Fuzzy Set ◽  
Fuzzy Entropy ◽  
Entropy Measure ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Entropy Measures ◽  
New Type ◽  
Definition Of ◽  
Multiple Attributes Decision Making ◽  
Interval Valued

We first show the interval-valued intuitionistic fuzzy entropy which reflects intuitionism and fuzziness of interval-valued intuitionistic fuzzy set (IvIFS) based on interval-valued intuitionistic fuzzy cross-entropy. As for intuitionism and fuzziness of IvIFS, we propose interval-valued intuitionistic entropy and interval-valued fuzzy entropy, respectively. Furthermore, we establish the interval-valued span entropy describing the uncertainty of membership degree and nonmembership degree and show some concrete measure formulas. Combining intuitionistic factor, fuzzy factor, and span factor, we ultimately put forward the axiomatic definition of the compositive entropy and give a measure formula of compositive entropy. In addition, the effectiveness of the compositive entropy measure is illuminated by comparison with other entropy measures. Furthermore, the compositive entropy is applied to multiple attributes’ decision-making by using the weighted correlation coefficient between IvIFSs and pattern recognition by a similarity measure transformed from the compositive entropy.

An Improved Axiomatic Definition and Structural Formula of Interval-Valued Intuitionistic Fuzzy Entropy

2014 ◽  
Vol 644-650 ◽  
pp. 1556-1559
Author(s):  
Ming Mei Gao ◽  
Tao Sun ◽  
Rui Ping Xu ◽  
Li Song ◽  
Hui Qun Zhang
Keyword(s):  
Structural Formula ◽  
Fuzzy Entropy ◽  
Axiomatic System ◽  
Computational Formula ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Entropy ◽  
Axiomatic Definition ◽  
Definition Of ◽  
New Formula ◽  
Interval Valued

In view of the defects of existing axiomatic definitions of interval-valued intuitionistic fuzzy entropy, an improved axiomatic definition of the interval-valued intuitionistic fuzzy entropy is presented and the corresponding formula is structured in the paper. Firstly, defects in three kinds of the axiomatic system of entropy of IVIFS are analyzed in detail respectively. New axiomatic entropy definition is proposed for the sake of more reasonable depiction of the fuzziness of IVIFS. Based on the new axiomatic entropy definition, a new computational formula is mentioned. Finally, an example is showed to illustrate the effectiveness of this new formula. Overall, the results indicate that the improved axiomatic definition and the new proposed formula are reasonable and effective.

On intuitionistic fuzzy order-α divergence and entropy measures with MABAC method for multiple attribute group decision-making

2021 ◽  
Vol 40 (1) ◽  
pp. 1191-1217
Author(s):  
Rajkumar Verma
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Entropy ◽  
Information Measures ◽  
Divergence Measures ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Entropy Measures

The development of information measures associated with fuzzy and intuitionistic fuzzy sets is an important research area from the past few decades. Divergence and entropy are two significant information measures in the intuitionistic fuzzy set (IFS) theory, which have gained wider attention from researchers due to their extensive applications in different areas. In the literature, the existing information measures for IFSs have some drawbacks, which make them irrelevant to use in application areas. In order to obtain more robust and flexible information measures for IFSs, the present work develops and studies some parametric information measures under the intuitionistic fuzzy environment. First, the paper reviews the existing intuitionistic fuzzy divergence measures in detail with their shortcomings and then proposes four new order-α divergence measures between two IFSs. It is worth mentioning that the developed divergence measures satisfy several elegant mathematical properties. Second, we define four new entropy measures called order-α intuitionistic fuzzy entropy measures in order to quantify the fuzziness associated with an IFS. We prove basic and advanced properties of the order-α intuitionistic fuzzy entropy measures for justifying their validity. The paper shows that the introduced measures include various existing fuzzy and intuitionistic fuzzy information measures as their special cases. Further, utilizing the conventional multi-attributive border approximation area comparison (MABAC) model, we develop an intuitionistic fuzzy MABAC method to solve real-life multiple attribute group decision-making problems. Finally, the proposed method is demonstrated by using a practical application of personnel selection.

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